2018Unpublished venueRequires access

Light Curve Analysis of Variable Stars in the SmallMagellanic System

Aritra Roy, Supervisors Prof. Tanuka Chattopadhyay, R. K. Nayak

Open publisher page 0 citations

Abstract

Future Surveys of variable stars demand new techniques not only to analyze their light curves but also to tag the variable stars according to their variability class in an automated way. We have collected a part of the largest sample of RR Lyrae stars, of which 39082 were detected toward the Large Magellanic Cloud and 6369 toward the Small Magellanic Cloud and along with these we have also collected 2574 Fundamental Cepheid. At first, we normalized the time points into phase points in the range [0, 1] by using a suitable conversion formula. We then interpolated the light curve intensities in short phase steps (0.01) within phase 0 to 1 to get 100 equi-spaced points of intensities for each light curve and then also normalized the intensities between 0 to 1 for each of the light curve both in I and V band. Once these matrices consisting of a 9270×100 arrays for I band and 8867×100 arrays for V band are prepared, we performed PCA and ICA on the same database of light curves. Our main objective of this project is to compare capabilities of Principal Component Analysis and Independent Component Analysis for classification accuracy for different classes of variable stars as it is already proved that the Principal Component Analysis method is much better than Fourier Decomposition method in order to classify the different classes of variable stars.

About this research paper

What this paper is about

Future Surveys of variable stars demand new techniques not only to analyze their light curves but also to tag the variable stars according to their variability class in an automated way. We have collected a part of the largest sample of RR Lyrae stars, of which 39082 were detected toward the Large Magellanic Cloud and 6369 toward the Small Magellanic Cloud and along with these we have also collected 2574 Fundamental Cepheid. At first, we normalized the time points into phase points in the range [0, 1] by using a suitable conversion formula. We then interpolated the light curve intensities in short phase steps (0.01) within phase 0 to 1 to get 100 equi-spaced points of intensities for each light curve and then also normalized the intensities between 0 to 1 for each of the light curve both in I and V band. Once these matrices consisting of a 9270×100 arrays for I band and 8867×100 arrays for V band are prepared, we performed PCA and ICA on the same database of light curves. Our main objective of this project is to compare capabilities of Principal Component Analysis and Independent Component Analysis for classification accuracy for different classes of variable stars as it is already proved that the Principal Component Analysis method is much better than Fourier Decomposition method in order to classify the different classes of variable stars.

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Future Surveys of variable stars demand new techniques not only to analyze their light curves but also to tag the variable stars according to their variability class in an automated way. We have collected a part of the largest sample of RR Lyrae stars, of which 39082 were detected toward the Large Magellanic Cloud and 6369 toward the Small Magellanic Cloud and along with these we have also collected 2574 Fundamental Cepheid. At first, we normalized the time points into phase points in the range [0, 1] by using a suitable conversion formula. We then interpolated the light curve intensities in short phase steps (0.01) within phase 0 to 1 to get 100 equi-spaced points of intensities for each light curve and then also normalized the intensities between 0 to 1 for each of the light curve both in I and V band. Once these matrices consisting of a 9270×100 arrays for I band and 8867×100 arrays for V band are prepared, we performed PCA and ICA on the same database of light curves. Our main objective of this project is to compare capabilities of Principal Component Analysis and Independent Component Analysis for classification accuracy for different classes of variable stars as it is already proved that the Principal Component Analysis method is much better than Fourier Decomposition method in order to classify the different classes of variable stars.

Key concepts: Light curve, RR Lyrae variable, Variable star, Stars, Cepheid variable, Principal component analysis, Large Magellanic Cloud, Physics

Related papers

Back to paper searchBrowse research topicsOriginal source
Light Curve Analysis of Variable Stars in the SmallMagellanic System — Research Paper | ScholarLens